Customer self service subsystem for classifying user contexts

ABSTRACT

A system and method for classifying user context in a customer self service system that performs resource search and selection and includes a context attribute database comprising types of user contexts and one or more context attributes associated with each user context for processing by the system, and context attribute function database comprising functions for computing values for each context attribute. The classifying system comprises a computing device for receiving a user query and a context vector comprising data associating an interaction state with the user and, processing the query and context vector against data included in the context attribute database and context attribute function database for predicting a particular user context. The classifier populates the user context vector with context parameters specifying a user interaction state for use in a subsequent resource search. The result of this invention is an ability to relieve the user of the nonproductive work of describing their context and the ability to improve the search value by including criteria derived from both data and behaviors in the general population which may be unknown to the user. The system and method is especially applicable for a self service system in a variety of customer self service domains including education, real estate and travel.

BACKGROUND OF THE INVENTION

[0001] 1. Field of the Invention

[0002] This invention relates generally to the field of customer selfservice systems for resource search and selection, and morespecifically, to a novel mechanism for classifying user contexts forfacilitating a more focused search and improving the relevance of queryresults for such a system.

[0003] 2. Discussion of the Prior Art

[0004] Currently there exist many systems designed to perform search andretrieval functions. These systems may be classified variously asknowledge management systems, information portals, search engines, dataminers, etc. However, providing effective customer self service systemsfor resource search and selection presents several significantchallenges. The first challenge for current systems with querycapability is that serving queries intelligently requires a large amountof user supplied contextual information, while at the same time the userhas limited time, patience, ability and interest to provide it. Thesecond challenge is that searching without sufficient context results ina very inefficient search (both user time and system resource intensive)with frequently disappointing results (overwhelming amount ofinformation, high percentage of irrelevant information). The thirdchallenge is that much of a user's actual use and satisfaction withsearch results differ from that defined at the start of the search:either because the users behave contrary to their own specifications, orbecause there are other contextual issues at play that have not beendefined into the search.

[0005] The prior art has separately addressed the use of the history ofinteraction with the user or their current service environment toprovide context for a resource search and selection system. The priorart also assumes the shallow context of a single user query streamfocused on a single topic. A major limitation of these approaches isthat they burden the user with providing substantial contextualinformation and, further that these systems are unable to apply specificuser context to improve resource selection for other users on the samesubject.

[0006] As will be hereinafter explained in greater detail, somerepresentative prior art search and retrieval systems include U.S. Pat.No. 5,974,412 entitled “Intelligent Query System for AutomaticallyIndexing Information in a Database and Automatically CategorizingUsers”; U.S. Pat. No. 5,600,835 entitled “Adaptive Non-Literal TextString Retrieval”; and U.S. Pat. No. 5,794,178 entitled “Visualizationof Information Using Graphical Representations of Context Vector BasedRelationships and Attributes”.

[0007] U.S. Pat. No. 5,974,412 describes an adaptive retrieval systemthat uses a vector of document and query features to drive the retrievalprocess. Specifically described is an Intelligent Query Engine (IQE)system that develops multiple information spaces in which differenttypes of real-world objects (e.g., documents, users, products) can berepresented. Machine learning techniques are used to facilitateautomated emergence of information spaces in which objects arerepresented as vectors of real numbers. The system then deliversinformation to users based upon similarity measures applied to therepresentation of the objects in these information spaces. The systemsimultaneously classifies documents, users, products, and other objectswith documents managed by collators that act as classifiers ofoverlapping portions of the database of documents. Collators evolve tomeet the demands for information delivery expressed by user feedback.Liaisons act on the behalf of users to elicit information from thepopulation of collators. This information is then presented to usersupon logging into the system via Internet or another communicationchannel.

[0008] U.S. Pat. No. 5,600,835 describes a method and system forselectively retrieving information contained in a stored document setusing a non-literal, or “fuzzy”, search strategy, and particularlyimplements an adaptive retrieval approach. A text string query istransmitted to a computer processor, and a dissimilarity value Di isassigned to selected ones of stored text strings representative ofinformation contained in a stored document set, based upon a first setof rules. A set of retrieved text strings representative of storedinformation and related to the text string query is generated, basedupon a second set of rules. Each of the retrieved text strings has anassociated dissimilarity value Di, which is a function of at least onerule Rn from the first set of rules used to retrieve the text string anda weight value wn associated with that rule Rn. The retrieved textstrings are displayed preferably in an order based on their associateddissimilarity value Di. Once one or more of the retrieved text stringsis chosen, the weight value wn associated with at least one rule of thefirst set of rules is adjusted and stored.

[0009] U.S. Pat. No. 5,794,178 describes a system and method forautomatically generating context vectors representing conceptualrelationships among information items by quantitative means for use instorage and retrieval of documents and other information items and fordisplaying them visually to a user. A neural network operates on atraining corpus of records to develop relationship-based context vectorsbased on word proximity and co-importance using a technique of “windowedco-occurrence”. Relationships among context vectors are deterministic,so that a context vector set has one logical solution, although it mayhave a plurality of physical solutions. No human knowledge, knowledgebase, or conceptual hierarchy, is required. Summary vectors of recordsmay be clustered to reduce searching time, by forming a tree ofclustered nodes. Once the context vectors are determined, records may beretrieved using a query interface that allows a user to specify contentterms, Boolean terms, and/or document feedback. Thus, context vectorsare translated into visual and graphical representations to therebyprovide user visualization of textual information and enable visualrepresentations of meaning so that users may apply human patternrecognition skills to document searches.

[0010] It would be highly desirable to provide for a customer selfservice system, a mechanism that applies user context for the purpose ofmore efficient resource dispersion.

[0011] It would be further highly desirable to provide a mechanism for acustomer self service system that applies user context for the purposeof more efficient resource dispersion and, that improves the relevanceof search results for a given user in their current context withoutrequiring the user to explicitly train the system.

[0012] It would be highly desirable to provide for a customer selfservice system, a mechanism that is able to improve the search value byincluding criteria derived from both data and behaviors in the generalpopulation which may be unknown to the user.

SUMMARY OF THE INVENTION

[0013] It is an object of the present invention to provide for acustomer self service system a mechanism that applies user context forthe purpose of more efficient resource dispersion.

[0014] It is a further object of the present invention to provide for acustomer self service system, a mechanism that applies user context forthe purpose of more efficient resource dispersion and, that improves therelevance of search results for a given user in their current contextwithout requiring the user to explicitly train the system.

[0015] It is another object of the present invention to providesupervised machine learning to a set of historical user interactionrecords to classify context attributes that are relevant for this userof the system.

[0016] According to the invention, there is provided a system and methodfor classifying user context in a customer self service system thatperforms resource search and selection and includes a context attributedatabase comprising types of user contexts and one or more contextattributes associated with each user context for processing by thesystem, and context attribute function database comprising functions forcomputing values for each context attribute. The classifying systemcomprises a computing device for receiving a user query and a contextvector comprising data associating an interaction state with the userand, processing the query and context vector against data included inthe context attribute database and context attribute function databasefor predicting a particular user context. The classifier populates theuser context vector with context parameters specifying a userinteraction state for use in a subsequent resource search.

[0017] The result of this invention is an ability to relieve the user ofthe nonproductive work of describing their context and the ability toimprove the search value by including criteria derived from both dataand behaviors in the general population which may be unknown to theuser.

[0018] Advantageously, such a system and method of the invention isapplicable for a customer self service system in a variety of customerself service domains including education, real estate and travel.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Further features, aspects and advantages of the apparatus andmethods of the present invention will become better understood withregard to the following description, appended claims, and theaccompanying drawings where:

[0020]FIG. 1 is a flowchart showing the steps of the control flowbetween the component inventions included in the generic preferredembodiment of the system invention.

[0021]FIG. 2 is a flowchart showing the generic process steps of theuser's interaction with the customer self service system through theiconic interfaces of the preferred embodiment of the invention.

[0022]FIG. 3 provides examples of data elements from the education, realestate and travel domains given example user interactions with thecustomer self service system via the iconic interfaces of the invention.

[0023]FIG. 4 illustrates the first Graphical User Interface 12 includingthe Context Selection Workspace 13.

[0024]FIG. 5 illustrates the second Graphical User Interface 22including the Detail Specification Workspace 23.

[0025]FIG. 6 is a flowchart showing the steps of control flow for theClassifying User Contexts sub-process according to the preferredembodiment of the invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0026]FIG. 1 illustrates a customer self service system (“system”) 10which is described in detail commonly-owned, co-pending U.S. patentapplication Ser. No. ______ entitled CUSTOMER SELF SERVICE SYSTEM FORRESOURCE SEARCH AND SELECTION (YOR8-2000-0932, Atty Dckt #14065) thecontents and disclosure of which are incorporated by reference as iffully set forth herein. The system 10 is a comprehensive self servicesystem providing an end-to-end solution that integrates the user andsystem, the content and context, and, the search and result so that thesystem may learn from each and all users and make that learningoperationally benefit all users over time. The present inventioncomprises a particular aspect of this system that focuses on improvingthe relevance of search results for a given user in their currentcontext without requiring the user to explicitly train the system.

[0027] Particularly, as shown in FIG. 1, the self service systemprovides a three-part intuitive iconic interface comprising interfacecomponents 12, 22 and 32 for visualizing and exploring the set ofresources that the system has found to match the user's initial queryand related subject and context variables. The system 10 preferablyenables the expression of a user's context as part of the query andexpresses the relevance of the results to a particular user via theinterface in terms beyond that of the results' content. The resource setis presented to the user in a way which clearly illustrates their degreeof fit with the user's most important context variables, as indicated bytheir prior usage of the system, as well as by context choices for thecurrent query. The system displays the resources in the sequencespecified by the user and enables the user to select and weight thecriteria to be used in interpreting and selecting between resources.This provides a shifting of the user's focus from finding something, tomaking choices among the set of resources available. Via the interfacecomponents 12, 22 and 32, the user may redefine their query, previewsome or all of the suggested resources or further reduce, and redisplaythe response set to extract those with the best degree of fit with thatuser's current needs. The system generates and displays via theinterface a listing of the currently active inclusionary andexclusionary content filters and provides a means for modifying them.More specifically, the intuitive user interface of the invention enablesusers to specify the variables of their resource needs.

[0028]FIG. 2 particularly depicts reduced-size displays illustrating thethree iconic user interfaces 12, 22, 32 which comprise the respectiveworkspaces according to the invention. As will be described in greaterdetail herein, the first graphical user interface 12 comprises aninitial Context Selection Workspace 13 that enables the expression ofuser context as part of a query in a manner optimized for ease of use;the graphical user interface 22 shown in FIG. 2 provides a DetailedSpecification Workspace 23 including a visual representation ofmulti-dimensional data for expressing query and results that enablesusers to completely manage their search in a manner optimized forsimplicity and clarity of logic; and, the graphical user interface 32 isdirected to a Results Display Workspace 33 that enables expression ofrelevance of results in terms of user context in a manner optimized tofacilitate resource selection using user supplied decision criteria.Aspects of interfaces 12, 22 and 32 shown in FIG. 2 are described ingreater detail in commonly-owned, co-pending U.S. patent applicationSer. No.______ entitled CUSTOMER SELF SERVICE ICONIC INTERFACE FORPORTAL ENTRY AND SEARCH SPECIFICATION (YOR8-2000-0929, Atty Dckt #14064)and additionally in commonly-owned, co-pending U.S. patent applicationSer. No.______ entitled CUSTOMER SELF SERVICE ICONIC INTERFACE FORRESOURCE SEARCH RESULTS DISPLAY AND SELECTION (YOR8-2000-0927, Atty Dckt#14072) the contents and disclosure of each of which are incorporated byreference as if fully set forth herein.

[0029] Referring back to FIG. 1, there is depicted a conceptual controlflow 10 for the customer self service resource search and selectionsystem according to a preferred embodiment. Via the three-part intuitivegraphic user interface (GUI) users are enabled to enter queries andmanipulate the system's responses according to their resource needs.Behind the scenes, as will be described, is a set of sub-systemcomponents that cooperate to derive, assume, sense and infer particularuser contexts with minimal user effort. These components includedatabases such as: 1) a Context Attributes Master database 14 whichstores the definitions of all the attributes known to the system andtheir relationships to predefined user contexts; 2) an Attribute ValueFunctions database 16 which stores the definitions and logic associatedwith assigning a value to an attribute for specific instances (contextdefault, groups of users); 3) a Resource Indexing Functions database 18which stores the definitions and logic for mapping specific resources tospecific context sets; and, 4) a historical User Interaction Recordsdatabase 15 which stores the users' prior queries, responses, andinteractions with the system 10. The first three databases are createdbefore system startup and the User Interaction Records 15 is createdwith the first user/use of the system, however, it is understood thatall four databases are maintained and enhanced through system operationsdescribed below.

[0030] First, prior to a user signing on to the system, and before theuser first views the iconic interface 12, the system 10 performs severalpre-processing steps including: 1) creating of an empty “user contextvector” 25 and populating the context vector with minimal informationfrom external data elements 11 integrated with the system or, fromsystem sensing/discovery; and, 2) processing the minimal user contextvector 25 against the Context Attributes database 14, the AttributeValue Functions database 16, and the User Interaction Records database15 using context classification logic to result in a “suggestion” thatthis particular user may be classified into one of a small number ofuser context definitions from the system's predefined long list ofcontext definitions. After these pre-processing steps, the first iconicinterface 12 is then displayed for the user at the user's terminal, orweb-browser, in the case of resource searches conducted over a web-basedcommunication link. The iconic Context Selection Workspace 13 initiallydisplays a small set of User Context Icons it has determined are mostappropriate, captures the user's selection of the one that seems mostfitting for the current user search session, and captures the user'sactual query. In most cases, this minimal entry will suffice to beginthe search because the system has already determined the relevantattributes, default values and parameters to drive the system forwardthrough the user search without any additional entry on the user's part.However, if the user wishes to review their defaults or to fine tunesome context or resource variables, there is an option to proceed to theiconic Detailed Specification Workspace display 22 before starting thesearch.

[0031] Regardless of the screen navigation path chosen, when the userinitiates the query, the system 10 packages the user query with adetailed User Context Vector 25 summarizing what is known of the user'sneeds at this point. Once the search is initiated, the query and contextvector are processed sequentially through three distinctsub-processes: 1) a Classifying User Contexts sub-process 24 accordingto the invention; 2) an Adaptive Indexing of Resource Solutions andResource Lookup sub-process 28; and, 3) a Response Set Ordering andAnnotation sub-process 34.

[0032] Particularly, the Classifying User Contexts sub-process 24,receives as input the user query and the raw context vector 25 andExternal User Data 11, and processes these against the User Interactionrecords 19 for this user/user group, data from the Context AttributesMaster 14 and Attribute Value Functions 16. The system classifies thisspecified user interaction state and annotates the context vector 25′with a complete set of context parameters for use in subsequentprocessing. The Classifying User Contexts sub-process 24 particularlyapplies an inductive learning algorithm as an attempt to predict derivedcontexts. Additionally, the Classifying User Contexts sub-process 24updates the Attribute Value Functions database 16 with more enhancedfunctions.

[0033]FIG. 6 illustrates the specific control flow of the ClassifyingUser Contexts sub-process 24 according to the present invention, andparticularly, the methodology implemented for classifying a specifieduser interaction state and annotating it with a complete set of contextparameters for use in the ensuing search processes. According to theinvention, the term “context” includes a very broad range of“attribute—value pairs” which describe a user, including, but notlimited to, their knowledge of a customer service domain, theirorganizational and community contexts, their user environments(including technology capabilities) and other items of static,historical or transient nature.

[0034] For the purpose of this invention the terms rule and function areused interchangeably. Both refer to any data structure that can beexecuted by an interpreter in a way as to compute a set of labeledoutput values given a set of labeled input values. An example of anarithmetic rule is “Fahrenheit<−Centigrade * 5/9+32”. Rule languagesinclude, but are not limited to: neural nets, decision trees, functionallanguages, polynomial functions.

[0035] To accomplish this task of classifying a specified userinteraction state and annotating it with context parameters for use inthe ensuing search, three asynchronous operations are executed: 1) afirst operation involving periodic data creation and maintenance; 2) asecond operation occurring frequently or continuously in the backgroundand involving system learning from historical transactions; and 3) athird operation that occurs when the user initiates or refines a queryto the system and necessarily requires both of first and secondoperations to execute as a prerequisite.

[0036] More particularly, in the first operation, 241 the system issupplied with an ever-improving “master” set of context attributes 14and associated functions 16 for assigning default values to thoseattributes. Particularly, the context attributes master 14 includes thename of the contexts, their attributes, and the icons for display viathe interface (FIG. 2) that represent each context and attribute. Thecontext attribute functions 16 are the software code that computesvalues for each of the context attributes. For example, when the selfservice system is implemented in an education capacity or domain, afunction may enumerate the list of people in a college or in-house classor, in a more complex example, it may look at the parameters surroundinga user's connectivity to see if it is low or high bandwidth, etc. It isunderstood that a startup set of attributes and functions 240 relate tooperational domains, e.g. education, real-estate, travel, and areinitially defined by system administrators and available at systeminitiation. On an ongoing basis, a sub-process, described incommonly-owned, co-pending U.S. patent application Ser. No.______(YOR8-2000-0930, Atty Dckt #14071), applies machine learning to theidentification of additional contexts and facilitates the systemadministrator's validation of contexts and creation of newly derivedcontext attributes in the master set 14. In most instances, functionsassociated with those attributes are automatically generated by acontext classifier process 29 a in the manner described herein. However,this Context Classifier process 29 a does enable the systemadministrator to manually input those functions explicitly at the sametime as validating the new context attributes proposed by the system.

[0037] In the second operation 242, the Context Classifier 29 a executesas a continuous, iterative, and potentially off-line process, i.e., itis not part of the control flow of processing a specific user query. TheContext Classifier 29 a applies an inductive learning algorithm toattempt to predict derived contexts. Particularly, for a particulardomain, the Context Classifier 29 a analyzes historical user interactionrecords 19 from the User Interaction Records database 15 to learn howthe user, the attributes and the specific values map to ContextAttribute functions 16, i.e., the user interaction records 15 serve as atraining set for the continuous improvement of the functions. Thissystem learning may be accomplished because the user interaction recordscontain traces of previous interactions, including user validatedcontexts that were applicable during those sessions, and the users'response/behaviors around those transactions. Additionally, the ContextClassifier 29 a considers both individual user history and that of otherusers with shared organization, community or environmental similaritiesleading to common behaviors and acceptance criteria. The output 247 ofthis process comprise the additions and modifications to the set ofContext Attribute functions 16 resulting in increasing ability topredict derived contexts as functions of the raw contexts.

[0038] In the third operation 243, a Context Applier process 29 b isexecuted on-line when the user initiates (logs-in) or refines a query tothe system. Each user's current inquiry transaction has it's own set ofraw contexts (as entered via the iconic interface or sensed in responseto the user log-in identification). As shown in FIG. 6, these rawcontexts include user context whether it be static, historical, ortransient, organizational or community context, environment context, orany other context associated with the user and dependent upon thatuser's interaction state and query domain, e.g., education, real estate,travel, etc. The Context Attribute functions 16 are used to compute aspecific value for each context pair, given the raw context 250 for thisparticular user transaction. Since the functions are constantlyimproving, the values computed for each context attribute for eachindividual user lead to improved accuracy and relevance in the searchthat follows.

[0039] The output of the Context Applier process 29 b is the ContextVector 25′ which holds all the context attributes and values relevant tothis search and which is used in the ensuing resource lookup asdescribed in commonly-owned, co-pending U.S. patent application Ser.No.______ (YOR8-2000-0928, Atty Dckt #14070) entitled CUSTOMER SELFSERVICE SUBSYSTEM FOR ADAPTIVE INDEXING OF RESOURCE SOLUTIONS ANDRESOURCE LOOKUP (YOR8-2000-0928, Atty Dckt #14070), the contents anddisclosure of which are incorporated by reference as if fully set forthherein. Importantly, this context vector is kept intact through thecompletion of the user search, even if later revised, so the system canlearn what leads to successful and unsuccessful search conclusions asdescribed in co-pending U.S. patent application Ser. No.______(YOR8-2000-0928, Atty Dckt #14070).

[0040] The Context Applier process 29 b is additionally invoked at eachsession initiation for a user's search transaction, using a minimal ornull user data set to produce defaults for user context, attributes,values, and resource parameters for the initial display of the interfacedescribed in co-pending U.S. patent application Ser. No.______(YOR8-2000-0929, Atty Dckt #14064). This pre-processing step deliversadditional benefits to the user by insuring use of the most current dataand functions operating in the system, i.e., the system will determineeverything about the user and generate the most up to date contextvextor before processing their actual user query. Described below withrespect to FIG. 3 are representative examples of a user's interactionwith the system in a variety of customer domains including education,real estate and travel. In the representative examples illustrated inFIG. 3, the Context Classifier will initially populate the user contextvector with the context attributes and associated values according to auser, for example, in response to user log-in to the system, orsubsequently, in response to initial query and context icon selection.

[0041] As the customer self service system is provided withfunctionality enabling a user to “bookmark” their stopping point in aprior session and to resume with a “work-in-process” data set, theinitial settings may be modified based upon system discovery or useroverride at the time of inquiry, resulting in the raw contextsassociated with the user's current inquiry transaction. It is this rawcontext data which serves as input to the Classifying User Contextssub-process 24.

[0042] The Adaptive Indexing of Resource Solutions and Resource Lookupsub-process 28 receives as input the user query and the context vector25′ and processes them against a Resource Library 42, the UserInteraction Records for this user/user group 19, and the ResourceIndexing Functions 27. This sub-process particularly maps specificcontexts to specific resources so as to increase the relevance of searchresults for a given user in their current context without requiring theuser to explicitly train the system. The primary output of the AdaptiveIndexing of Resource Solutions and Resource Lookup sub-process 28 is anewly identified Resource Response Set 35 which is input to the ResponseSet Ordering and Annotation sub-process 34. The Adaptive Indexing ofResource Solutions and Resource Lookup sub-process 28 additionallygenerates a secondary output which comprises updates to the ResourceIndexing Functions database 18 with yet more enhanced functions 27′.Further details regarding the Adaptive Indexing of Resource Solutionsand Resource Lookup sub-process 28 may be found in commonly-owned,co-pending U.S. patent application Ser. No.______ (YOR8-2000-0928, AttyDckt #14070).

[0043] The Response Set Ordering and Annotation sub-process 34 receivesas input the User Context Vector and Resource Response Set 35 andprocesses it against data from an Annotation Scoring Metric database 46and User Interaction Records 19 for the particular user/group. Thissub-process 34 weights and ranks the potential responses according tothe resource selection criteria specified by the user on the DetailedSpecification Workspace described herein, and takes into considerationthe scoring metric. The sub-process 34 additionally tags the responseset with data elements necessary for display and manipulation on avisualization system, including, but not limited to, the Results DisplayWorkspace 32 described in the co-pending U.S. patent application Ser.No.______ (YOR8-2000-0927, Atty Dckt #14072), and particularly generatesas output an Annotated Resource Response Set 38. Further detailsregarding the Response Set Ordering and Annotation sub-process 34 may befound in commonly-owned, co-pending U.S. patent application Ser.No.______ (YOR8-2000-0931, Atty Dckt #14068), the contents anddisclosure of which are incorporated by reference as if fully set forthherein.

[0044] As mentioned, the ordered and annotated set of resources that thesystem has found to best match the user's initial query and relatedsubject and context variables may be utilized to drive a visualizationsystem, including but not limited to, the intuitive iconic interface 32for visualizing and exploring the response set as will be described ingreater detail herein. This Results Display Workspace provides aninterface that enables the user to continue working to learn about theresources suggested (detail/preview), narrow their results (selection)or redisplay them in a more meaningful view for decision making(graphically). In most instances, that will suffice. However, should theuser wish to further refine their query, tune or override their currentor default settings, that option is also available by navigating back tothe Detailed Specification Workspace interface 22. If the user needs tostart over, including selection of a new user context, it will benecessary to navigate back to the initial Context Selection Workspace13.

[0045] As the user works with the system, particularly through theResults Display Workspace 32 and the Detail Specification Workspace 22his/her interactions are captured and stored in the User InteractionRecords database 15. Thus, in addition to the user query, context vectorand response data set, the system retains adjustments to user context,results display manipulation, and results viewing and selection behavior51.

[0046] Having completed the transaction, there is one more sub-processwhich is essential to this system: the sub-process for Context ClusterDiscovery and Validation 48. This batch process, occurringasynchronously and constantly, applies unsupervised (machine) learningto cluster user interaction records and to assist in the identificationof new user contexts, attribute value functions and resource indexingfunctions. The User Interaction Records 19 are processed against theContext Attributes Master database 14, the Attribute Value Functionsdatabase 16 and the Resource Indexing Functions database 18 and aDistance Metric 44 which helps determine “how close is close”, i.e.,“what's good enough” for a variety of factors. When validated by asystem administrator, additional user contexts may be implemented(manually or semi-automatically) in the databases and visibly as newicons on the Context Selection Workspace 13.

[0047] Attribute value functions may also be identified and resourceindexing functions may be discovered and updated in the appropriatefiles automatically. All of these additional classifications improve theease of use, accuracy, and predictability of the system over time.Further details regarding the Context Cluster Discovery and Validationsub-process 48 may be found in commonly-owned, co-pending U.S. patentapplication Ser. No.______ entitled CUSTOMER SELF SERVICE SUBSYSTEM FORCONTEXT CLUSTER DISCOVERY AND VALIDATION (YOR8-2000-0930, Atty Dckt#14071), the contents and disclosure of which are incorporated byreference as if fully set forth herein.

[0048] The customer self-service system and the interaction with thesystem through the iconic interfaces of FIGS. 4 and 5, will be describedwith respect to example domains such as education, travel and realestate, and further will be described from the point of view of thefollowing users: a learner, a traveler and a real estate transactor,e.g., renter/buyer. In describing the user's interaction with the systemthrough the iconic interfaces, a set of data elements used in the systemand their characteristics are first defined as follows:

[0049] Query: an entry field for entering search data by using text orvoice methods, for example, but not limited to these methods

[0050] User Context: a User Context represents a predefined set ofcontext attributes which are relevant to the search behavior/needs of agroup of people.

[0051] More particularly, the User Context enables the packaging of arich set of attributes about the user with a rich set of attributesabout their searching and execution environment in response to “oneclick” of an icon for the user presented via the interface. While thereare potentially a large number of potential user contexts for any userpopulation, each individual user would likely settle on a small numberthat apply to them in different circumstances. The naming of thesecontexts is important so that the user may recognize him/herself aspotentially fitting into that group. The attributes associated with aparticular user context are predefined by system administration andcannot be modified by the user. Over time, the system will identifychanges to the attribute set that will make a particular user contextperform better for its repeated users. Over time the system will detectdifferent attribute sets which appear to predict user needs/behaviorsand might suggest new user contexts for the system.

[0052] Context Attribute: An attribute is used to describe acharacteristic associated with the User Context.

[0053] There are potentially an unlimited number of attributes definedto the system with a master list maintained in the Context AttributesMaster File. New attributes are discovered and added with systemadministrator validation. End users may not modify the definition of acontext attribute, nor its' packaging into user contexts, nor the listof values associated with each.

[0054] Attribute Value: A list of attribute value choices is predefinedfor each context attribute.

[0055] The system sets a default value to each attribute based upon datalookup, sensed, or historically derived from prior user entry orbehavior. Either the system or the user may modify the value initiallyset based upon explicit preferences or observed behavior. This value isadded to the context vector used for resource lookup, and is retained inthe historical User Interaction Records database 15 so it may be used toset default values for each individual each time they use the system.

[0056] Value Resource Parameters: Parameters defined in terms ofinclusion and exclusion that may be used as a filter to increase therelevance of the response set.

[0057] That is, with the basic search logic established, the user'squery may be satisfied. However, the response set may contain a largenumber of resources which are not satisfactory to this individual. ValueResource Parameters defined in terms of inclusion and exclusion may beused as a filter to increase the relevance of the response set. Theinclusionary parameters may be easier to establish by users new to thesystem and that exclusionary parameters will become more evident asusers gain experience in working with the response sets.

[0058] Resource Selection Criteria and Value Ranges: Parameters andspecifications for ranking a user's response set to enable more informedresource selection.

[0059] Thus, even with the degree of specificity enabled by the system,and even with the constant improvement in search relevance/efficiency asit relates to user contexts, there usually may be more than one resourceto present to the user (in fact, if the search is too narrow, the usermay miss the opportunity to explore/discover different approaches tomeeting their actual needs). As most users know (or think they know) thecriteria they will apply to selecting between options, a limited set ofresource selection criteria are provided by the system (the set woulddiffer by domain). However, via an interactive graphical displayprovided by the iconic interface of the invention, the user may nowspecify acceptable value ranges and relative weighting of each criteriafor ranking their response set and/or may customize the use of thesecriteria.

[0060] When the actual response set data is offered, most users face thereality of many options, few options, more subjective information aboutspecific resources; and they may make tradeoffs around the selectionlogic. For example, the response set may be refreshed as the user maydecide to eliminate a criteria, change the weight of a criteria, orchange the acceptable value ranges for a criteria. From thesespecifications, accessible via the iconic interface of the invention,the user may determine for example, whether time, timing, flexibility,and risk may be sacrificed in order to bring the cost down below acertain dollar ($) value, and, for example, determine how much morewould the user need to pay to get exactly what he/she wants exactly whenhe/she wants it.

[0061]FIGS. 2, 4 and 5 depict in greater detail the iconic interfacesfor the customer self service system that enable the use of a rich setof assumed, sensed, inferred, and derived contexts with minimal usereffort.

[0062] With initial logon, as shown in FIG. 2, the system first presentsa set of user contexts which are available to the user via thesimplified iconic interface 12 of FIG. 2. The system will suggest onecontext over the others, but the user may select the one mostappropriate to their current situation. In each session, the userselects only one user context to use, however over time each user maydiscover that a couple of different user contexts serve their needs indiffering circumstances. On this screen 13 particularly, the user thenenters a query via one or more methods including text via a web browserdisplay interface, for example, or via voice, for example, with help ofvoice recognition software. It should be understood however, that queryentry is not limited to these types of methods. The user will theninitiate a lookup and proceed either to a third process step (via mostdirect path 52) for viewing a search result response set via the ResultsDisplay Workspace interface 32, or, proceed to a second step (via path50) to optionally refine/override search variables via the DetailSpecification Workspace interface 22. FIG. 4 illustrates in detail thefirst graphical user interface 12 including the initial ContextSelection Workspace 13 that enables the expression of user context aspart of a query. As shown in FIG. 4, the Context Selection Workspace 13includes: a series of one or more selectable User Context Icons 132presented to the user for selecting user contexts; and, a Query EntryField 131 enabling user entry of search terms via text or voice entry,for example. In accordance with the principles of the invention, theUser Context Icons 132 are graphical user interface elements from whichthe user selects the one context most representative of his/her currentsituation. The icons presented in this interface each represent apackaging of sets of attribute-value pairs which describe a kind of userin a particular situation. Particularly, a user context represents apredefined set of context attributes which are relevant to the searchbehavior/needs of a group of users. For example, as described herein,context may include aspects of the user's knowledge, their relationshipto organizations and/or communities, their user environment(s), andtheir resource need. All of these combine to provide a rich contextsurrounding the actual query which can significantly improve the outcomeof the search through resources.

[0063] The Context Selection Workspace 13 thus enables the expression ofuser context as part of the query and is optimized for ease of use.Particularly, the user selects from one or more of the several displayedcontext icons 132 by clicking on them. A context “applier” pre-processdescribed in commonly-owned, co-pending U.S. patent application Ser.No.______ (YOR8-2000-0929, Atty Dckt #14069) is invoked at each sessioninitiation for a user's search transaction, using a minimal or null userdata set to produce defaults for user context, attributes, values, andresource parameters for the initial display of the Context SelectionWorkspace 13. This pre-processing step delivers additional benefits tothe user by ensuring the use of the most current data and functionsoperating in the system. After making the initial query entry, byselecting hyperlink 134, the user is able to initiate the search andproceed directly to the third interface 32 which displays the actualsearch results. Alternately, by selecting hyperlink 136, the user mayproceed to the second interface 22 having the Detail SpecificationWorkspace 23 for further query editing and/or context refinement.

[0064] Returning to FIG. 2, with respect to the second step, the user isable to fine tune or override context attribute values, value resourceparameters, and resource selection criteria and value ranges, using adrag and drop interface, iconic pulldowns, and/or slide buttons. Theuser may return to this screen as many times as needed to find asuitable response set. Particularly, via the second iconic interface 22,the User Context selected in the first step has been made explicit byits default settings on all the iconic interface elements listed. Thus,via a Detail Specification Workspace 23 the user may: 1) modify thequery (via text entry or voice, for example); 2) change the value ofattributes associated with the user context (using pull down menus);alter the value resource parameters (e.g., include/exclude) usingcheckboxes; 3) customize the subset of responses by altering theresource selection criteria, including the weighting of criteria and theordering of criteria on the final display, (e.g., using checkbox and/ornumeric entry); and, 4) further refine the selection by specifyingminimum/maximum acceptable value ranges for resource selection criteriathrough drag and drop of “tabs” on sliders, for example. After makingthe necessary adjustment, the user re-initiates the lookup and mayproceed to the third step via path 51.

[0065]FIG. 5 illustrates in detail aspects of the second iconicgraphical user interface 22 which enables the user to define or changeall the parameters associated with their query 131 and (single) selecteduser context 132. As shown in FIG. 5, the graphical user interface 22 isdivided into the following sections: a section for displaying the QueryEntry field 131 as entered on the prior interface screen (FIG. 4) andavailable for editing; a section for displaying navigation arrows whichallow the user to proceed with the search 134, or return to the initialContext Selection screen 136 via the first iconic interface to initiatea new query or select a different user context; and, a DetailedSpecification Workspace 23 which is where all the search parameters canbe explicitly viewed and modified. There are only two things the usercannot change from this screen: the user context selected (which theymay change only on the Context Selection screen) and the contextattributes which are linked to the user context (and which arepredefined in the Context Attributes Master database 14).

[0066] As shown in FIGS. 5, within the Detailed Specification Workspace23 there comprises: an Attribute-Value Workspace 231, for enabling theuser to change the attribute values for all the context attributes,represented as graphic elements 232, associated with the selected usercontext icon 132 (FIG. 4); and, a Resource Selection Criteria Workspace238, for enabling the user to define the criteria 245 to be used inevaluating resources, define minimum and maximum acceptable valuesprovided on slider elements 250 corresponding to each criteria, specifythe weight assigned to those criteria via selection boxes 242, andspecify the positioning of those criteria in a graphical display of theresources selected via selection boxes 241. As will be described, FIG. 3provides sample data for the context attribute, attribute value, valueresource parameters, and partial resource selection criteria fromdifferent domains which may be represented in the Detailed SpecificationWorkspace 23.

[0067] With more particularity, the Detailed Specification Workspace 23additionally includes the Value-Resource Parameter Workspace 235, forenabling the user to change or create resource parameters using includelogic 237 or exclude logic 239 for any attribute value 232 selected inthe Attribute-Value Workspace 231. More specifically, theAttribute-Value Workspace 231 includes graphical representations of allthe context attributes 232 associated with the single (currently active)selected user context 132. Each context attribute 232 is displayed witha text title 233 for the attribute. The currently active attribute valuefor that context attribute is shown on each context attribute icon. Inaddition, if the user has substituted, as described below, a contextattribute value different than the default value provided for this usersession, a marker 253 is displayed on the corner of the contextattribute icon. If the user “mouse clicks” on the context attributeelement, e.g., icon 232 b, the system displays a pull down menu 234 ofgraphic elements showing all the possible attribute values for thiscontext attribute. If the user “mouses over” any of the values from pulldown menu 234, e.g., attribute value 236, a textual description 236′supporting the element may appear. By selecting a context attributeelement from the pull down menu 234, e.g., element 236 shown highlightedin FIG. 5, the user is enabled to fine tune their selected context basedupon their current situation. If the user “mouse clicks” on a valueother than the current default, the new value is “selected” tosubstitute for the default. If the user “double clicks” on the attributevalue, the system prepares the Value-Resource Parameter Workspace 235for this single attribute value, as will be described. FIG. 3 providessample data for context attributes and attribute values from differentdomains which may be represented in the Attribute Value Workspace 231.

[0068] In the Value-Resource Parameter Workspace 235, the user maychange or create resource parameters using include logic or excludelogic for any context attribute value 232 selected in the workspace 231.Regarding FIG. 5, with more particularity, the Value-Resource ParameterWorkspace 235 is displayed for one attribute value at a time and is onlydisplayed when requested via a double click, for example, on one of theattribute values displayed in the attribute Value Workspace 231, e.g.,attribute value 236. The Value-Resource Parameter Workspace 235 is apre-formatted two-column space (dialog box) where the user may establishinclusionary resource filters via checkboxes 237 and/or exclusionaryresource filters via checkboxes 239, based upon pre-established resourcecharacteristics 236″ for that selected attribute value. The valueresource parameter data elements are pre-set by the user's know context,prior history of selecting from resources identified by the system, andpotentially by corporate/organizational policy implemented through thesystem. By making these additional specifications, the user is enabledto increase the relevance of the resource response set based upon theircurrent situation and personal preferences. When finished with thesespecifications, the user may double click to close this box 235 andreturn to the Attribute Value Workspace 231. This step can be repeatedfor as many attribute values as the user would like to refine and may beexecuted either before or after the search is conducted. Value resourceparameter data elements associated with context attribute values fordifferent domains, are provided in FIG. 3 as samples of data which maybe represented in this Value-Resource Parameter Workspace 235.

[0069] Regarding FIG. 5, with more particularity, the Resource SelectionCriteria Workspace 238 includes a list of criteria 245 which may be usedin evaluating resources. This list, provided by the system, iscustomized by domain; but in all domains, it involves criteriaincluding, but not limited to issues such as: cost, time, timing,quality and risk associated with using a particular resource to satisfythe user's specific need. The initial system default might be to use allcriteria and weight them equally. Over time, however, the defaultcriteria may be set by the system based upon user context, user priortransaction history and user behavior on prior searches. If the userwishes to further reduce the set of criteria, they may do so byassigning a weight, for example a percentage weight, to each criteriathey want used in the entry boxes 242. Along with each of the criteriaselected there exists a range of acceptable values specified on anassociated individual slider element 250. The initial system default,may be “unlimited” and then, may set over time based upon user context,use and behavior. Additionally, the user may use drag and drop tabs 252a, b on the slider element 250 to set a minimum and/or maximum value forthe associated resource selection criteria. It is understood that theunit of measure on the sliders may vary by criteria. Further, via entryboxes 241, the user may select to view via “check” or specify via numberentry the display sequence of these criteria when arrayed as the axes onan n-dimensional graphic display provided in the Results DisplayWorkspace via graphic interface 32 as described in commonly owned,co-pending U.S. patent application Ser. No.______ (YOR8-2000-0927, AttyDckt # 14072), or when viewed on another visualization system.

[0070] The Detailed Specification Workspace 23 thus provides fulldisclosure of system defaults and enables the user to completely managetheir search.

[0071] With respect to the third step, a display of the annotatedresponse set is provided in a form ready for preview or selection asdescribed herein. The user may rework this screen as many times asneeded to better understand and make decisions about resource(s) to use.More particularly, via the Results Display Workspace 33 the user may: 1)view the response set, ranked by the aggregate value and weighting asdefined by resource selection criteria and value ranges; 2) select oneor many of the ranked responses for graphical display inmulti-dimensions along the multiple axes of the resource selectioncriteria; and, 3) initiate a “roll over” of one or more resources fromeither the ranked list or the graphical display to view detaileddescriptions or to “preview” the resource. If there are too manyresponses, too few, or if they are incorrect, the user may return to thesecond step to further refine/redefine, and re-execute the lookup.Alternately, the user may return to the first step to choose a differentcontext for their search.

[0072] While the system is intended to operate on a fully enabledgraphic workstation or personal computer, it is intended that searchdefinition and the results visualization processes described herein maybe operated by users of reduced graphics-enabled devices such as textscreen workstations, Organizers, or any type of Personal DigitalAssistants (PDAs). Accordingly, in alternative embodiments, all thecontext icons may have names, all the graphical displays may be reducedto lists, all the pull downs may be viewed as indented lists orsecondary screens, and all the min-max sliders may convert to fill-inboxes. Further, as mentioned, the customer self service system describedherein is applicable to many applications including the domains ofeducation, real estate, and travel. The generic process flow describedwith respect to FIG. 2, will now be described with specific examplesfrom the education, real estate and travel domains as shown in FIG. 3.

[0073] With respect to the education domain, the user is a learner andFIG. 3 depicts an example interaction with the system through the iconicinterfaces (FIG. 2) included in the embodiment of the invention asapplied to the education domain. The three iconic workspaces of FIG. 2enable the learner to specify example data elements, such as the exampledata elements depicted in the Education (e.g., Environmental) column 60of FIG. 3, and view results, as follows: In the first process step, thelearner uses the Context Selection Workspace (interface 12 of FIG. 4) tospecify their query 61 as “Learn Lotus Notes at home.” The learner mayselect the User Context “Remote Staffie”, for example (where the icon'sname is highlighted in FIG. 3), from among the available set of contexticons 62. The learner may then elect to go to the Detail SpecificationWorkspace (interface 22 of FIG. 5) in the second process step in orderto view the context attributes 63 associated with the “Remote Staffie”User Context. Preferably, the default assigned context attribute value(“DSL”, for example) for any context attribute (“Connectivity”, forexample) is visible on the context attribute icon (“Connectivity”, forexample, whose name is shown highlighted in FIG. 3). The learner mayclick on the context attribute “Connectivity” to see the menu ofassociated attribute values 64. The learner, for example, may select the“Disconnected” attribute value shown highlighted in FIG. 3. By doubleclicking on this attribute value the list of Value Resource Parameters,i.e., include/exclude filters 65, for the attribute value “Disconnected”is displayed. The learner, for example, may indicate that they want toinclude download and play resources and exclude online collaborativeresources when searching for relevant resources. The learner mayadditionally specify resource priorities 66 by selecting, sequencing andweighting and specifying minimum and maximum values for relevantcriteria such as cost, time, quality and risk on the Resource SelectionCriteria Definition graphical user interface element on the DetailSpecification Workspace (interface 22 of FIG. 5). In the third step ofthe process, the results of the learner's search are listed in the userview of the Results Display Workspace (interface 32 of FIG. 2). Thelearner may immediately select one or more of the listed educationresources, request to see additional details on them, or request to seea response set graphic indicating the relative positioning of eachresource along each of the axes (n-dimensions, relating to cost, time,quality and risk) specified earlier. If no acceptable educationresources were provided, the learner may return to the Context Selection

[0074] Workspace to redefine their query or select a different UserContext such as “Commuting Techie” via the first interface. The learnermay additionally elect to return to the Detail Specification Workspaceof the second interface to change the default value of the contextattribute “Connectivity” from Disconnected to Dial-up and add or removeValue Resource Parameters for the attribute value Dial-up or othercontext attribute values associated with context attributes such as“Learning Mode” or “Technical Field”. The learner may also change theirselection criteria, the weighting of the selection criteria, and theminimum/maximum values for any selection criteria, in hopes ofidentifying additional relevant resources.

[0075] With respect to the education domain, the user is a “learner”however, the three iconic workspaces of FIG. 2 provide the process forenabling the learner to specify example data elements, such as theexample data elements depicted in the Education (e.g., Subject Matter)column 70 of FIG. 3, and view results, as follows: In the first processstep, the learner uses the Context Selection Workspace (interface 12 ofFIG. 4) to specify their query 71 as “Become a Linux developer by June”for example. The learner selects the User Context “Commuting Techie”from among the available context icons 72. The learner may elect to goto the Detail Specification Workspace in order to view the contextattributes 73 associated with the “Commuting Techie” user context.Preferably, the default assigned context attribute value (“Programming”,for example) for any context attribute (“Technical Field”, for example)is visible on the context attribute icon (“Technical Field”, forexample, whose name is shown highlighted in FIG. 3). In addition, thelearner may click on the context attribute (“Technical Field, to staywith the example) to display a pull down menu to view the other values74 (in either picture or word format) that could be assigned to thisattribute. The learner, for example, may select “Graphical Interfaces”shown highlighted in FIG. 3. By double clicking on this attribute value,the list of Value Resource Parameters (include/exclude filters 75) forthe attribute value “Graphical Interfaces” will be displayed. Forexample, the learner may indicate that they want to include the KDEinterface and exclude the GNOME interface when searching for relevantresources. The learner may additionally specify resource priorities 76by selecting, sequencing and weighting and specifying minimum andmaximum values for relevant criteria such as cost, time, quality andrisk on the Resource Selection Criteria Definition graphical userinterface element on the Detail Specification Workspace. The results ofthe learner's search are listed on the Results Display Workspace via theinterface 32. The learner may immediately select one or more of thelisted education resources, request to see additional details on them,or request to see a response set graphic indicating the relativepositioning of each resource along each of the axes (n-dimensions,relating to cost, time, quality and risk) specified earlier. If noacceptable education resources were provided, the learner may return tothe Context Selection Workspace 13 via the first interface 12 toredefine their query or select a different user context such as“Traveling Consultant.” The learner may also elect to return to theDetail Specification Workspace via the second interface 22 to change thedefault value of the context attribute “Technical Field” from GraphicalInterfaces to Programming and add or remove Value Resource Parametersfor the attribute value Programming or other context attribute valuesassociated with context attributes such as “Learning Mode” or“Connectivity.” The learner may also change their selection criteria,the weighting of the selection criteria, and the minimum/maximum valuesfor any selection criteria, in hopes of identifying additional relevantresources.

[0076] With respect to the real-estate domain, the user is a real estatetransactor (renter/buyer) and FIG. 3 depicts an example interaction withthe system through the iconic interfaces (FIG. 2) included in theembodiment of the invention as applied to the real estate domain. Thethree iconic workspaces of FIG. 2 enable a real estate renter or buyerto specify example data elements, such as the example data elementsdepicted in the Real Estate column 80 of FIG. 3, and view results, asfollows: In the first process step, the renter or buyer uses the ContextSelection Workspace to specify their query 81 as “Find housing near newjob by August.” The renter or buyer selects the user context “RelocatingBusiness Professional” from among the available context icons 82. Therenter or buyer may elect to go to the Detail Specification Workspace inthe second interface in order to view the context attributes 83associated with the “Relocating Business Professional” user context.Preferably, the default assigned context attribute value (“Subcontractit all”, for example) for any context attribute (“Maintenance Style”,for example) is visible on the context attribute icon (“MaintenanceStyle”, for example, whose name is shown highlighted in FIG. 3). Inaddition, the renter/buyer may click on the context attribute(“maintenance style, to stay with the example) to display a pull downmenu to view the other values 84 (in either picture or word format) thatcould be assigned to this attribute. Upon renter or buyer doubleclicking on attribute value “Do-It-YourSelf-er”, for example, the listof Value Resource Parameters (include/exclude filters 85) for theattribute value “Do-It-YourSelf-er” is displayed. For example, as shownin FIG. 3, the renter or buyer may indicate that they want to includewalls, paint and lawn mowing and exclude plumbing, electrical andlandscaping when searching for relevant resources. The renter or buyermay additionally specify resource priorities 86 by selecting, sequencingand weighting and specifying minimum and maximum values for relevantcriteria such as cost, time, quality and risk on the Resource SelectionCriteria Definition graphical user interface element on the DetailSpecification Workspace. The results of the renter or buyer's search arelisted on the Results Display Workspace of the third interface 32 inwhich the renter or buyer may immediately select one or more of thelisted real estate resources, request to see additional details on them,or request to see a response set graphic indicating the relativepositioning of each resource along each of the axes (n-dimensions,relating to cost, time, quality and risk) specified earlier. If noacceptable housing resources were provided, the renter or buyer mayreturn to the Context Selection Workspace to redefine their query orselect a different user context such as “Empty Nester.” The renter orbuyer can also elect to return to the Detail Specification Workspace tochange the default value of the context attribute “Maintenance Style”from Do-It-Yourself-er to Subcontract It All, for example, and add orremove Value Resource Parameters for the attribute value “Subcontract ItAll” or other context attribute values associated with contextattributes such as “Mode of Commute to Work/School” or “Mode ofHousing.” The real estate transactor may also change their selectioncriteria, the weighting of the selection criteria, and theminimum/maximum values for any selection criteria, in hopes ofidentifying additional relevant resources.

[0077] With respect to the travel domain, the user is a traveler andFIG. 3 depicts an example interaction with the customer self servicesystem through the iconic interfaces (FIG. 2) included in the embodimentof the invention as applied to the travel domain. The three iconicworkspaces of FIG. 2 enable a traveler to specify data elements, such asthe example data elements depicted in the Travel column 90 of FIG. 3,and view results, as follows: In the first process step, the traveleruses the Context Selection Workspace to specify their query 91 such as“Plan a trip to Vermont in June”, for example. The traveler may thenselect the User Context Icon “Single Mom with kids”, for example, fromamong the available user context icons 132, (where the icon's name 92 ishighlighted in FIG. 3). The traveler may then elect to go to the DetailSpecification Workspace in order to view the context attributes 93associated with the “Single Mom with Kids” user context. Preferably, thedefault assigned context attribute value (“Drive”, for example) for anycontext attribute (“Mode of Transportation”, for example) is visible onthe context attribute icon (“Mode of Transportation”, for example, whosename is shown highlighted in FIG. 3). In addition, the traveler mayclick on the context attribute (“mode of transportation ”, to stay withthe example) to display a pull down menu to view the other values 94 (ineither picture or word format) that could be assigned to this attribute(“Fly” for example). The traveler selects “fly” as an alternative to“drive”, as illustrated with highlighting in FIG. 3. By “overriding ”this attribute value and double clicking on it, the list of ValueResource parameters (include/exclude filters 95) for the attribute value“Fly” is displayed. The traveler may indicate that he/she wants toinclude all major carriers and exclude prop planes and airlines with badsafety records when searching for relevant resources. The traveler mayalso specify resource priorities 96 by selecting, sequencing andweighting and specifying minimum and maximum values for relevantcriteria such as cost, time, quality and risk on the Resource SelectionCriteria Definition graphical user interface element on the DetailSpecification Workspace. The results of the traveler's search are thendisplayed via the Results Display Workspace of the third iconicinterface 32 of FIG. 2. The traveler may immediately select one or moreof the listed travel resources, request to see additional details onthem, or request to see a response set graphic indicating the relativepositioning of each resource along each of the axes (n-dimensions,relating to cost, time, quality and risk) specified earlier. If noacceptable travel resources were provided, the traveler may return tothe Context Selection Workspace in Step 1 to redefine their query orselect a different user context such as “Swinging Singles.” The travelermay also elect to return to the Detail Specification Workspace in Step 2to change the default value of the context attribute “Mode ofTransportation” from Fly to Train and add or remove Value ResourceParameters for the attribute value Train or other context attributevalues associated with context attributes such as “Mode of Housing” or“Food Style”. The traveler may also change their selection criteria, theweighting of the selection criteria, and the minimum/maximum values forany selection criteria, in hopes of identifying additional relevantresources.

[0078] Referring back to FIG. 1, the customer self service systemimplements an n-dimensional context vector 25′, derived from thecombination of user context and previous interaction with the system, tomap specific contexts to specific resources. This increases therelevance of search results for a given user in their current contextwithout requiring the user to explicitly train the system. Inferencesand conclusions are made regarding both the individual user's preferredresource characteristics and those of a common set of users. These areused as input to the sub-processes described above and in greater detailin above-mentioned commonly-owned, co-pending U.S. patent applicationSer. Nos.______ (YOR8-2000-0928, Atty Dckt #14070), and (YOR8-2000-0931,Atty Dckt #14068), to modify the iconic interfaces presented to eachparticular user for their subsequent search using the current inventionas well as to modify the results that would be selected for presentationto the user via the interface described in ______ (YOR8-2000-0927, AttyDckt #14072) in response to an identical search. Over time, the systemwill improve in its ability to serve individual needs and evolve to anability to suggest preferred answers to groups of users.

[0079] The overall system also uses a batch background process describedin commonly-owned, co-pending U.S. patent application Ser. No.______(YORb 8-2000-0930, Atty Dckt #14071) to cluster user interaction recordsto assist in the identification of new user contexts which serves toimprove the system over time.

[0080] While the prior art has made use of adaptive learning ininformation retrieval systems, the overall customer self service systemfor resource search and selection enables the use of a large, rich setof contextual attribute-value pairs, is focused on learning about theuser/user groups rather than the resources/resource groups and is ableto discover user group characteristics and apply them to individuals.Much of the prior art is focused on the discovery of database structure,the clustering of data within the resources, or discovering relevanttaxonomy for resources but the current system discovers contexts andcontext attributes among users which can be used predictively. Thecustomer self-service system of the invention uses a highly specializedand optimized combination of supervised and unsupervised logic alongwith both automated and semi-automated entry of learned results and isable to deliver higher value because contexts are used in a closed loopself improvement system; front end (entry) middle (search and display)and back end (results and user feedback) are integrated. Other systemsapply machine learning at the front, middle, or back, but not integratedthroughout. The current system identifies context classifications andfunctions, and applies them to individual users to reduce the burden offully communicating their question and increasing the specificity andaccuracy of a query's search parameters. The current system identifiesand improves selection logic and identifies and improves response setsto common queries based upon a rich set of contextual variables. Thecurrent system additionally orders the response set, potentially furtherlimiting it, and prepares the response set for display in a way thatidentifies the “best” resources for a particular user based upon therich set of context variables. The display of the invention additionallyillustrates the decision making characteristics of the alternativespresented.

[0081] While the invention has been particularly shown and describedwith respect to illustrative and preformed embodiments thereof, it willbe understood by those skilled in the art that the foregoing and otherchanges in form and details may be made therein without departing fromthe spirit and scope of the invention which should be limited only bythe scope of the appended claims.

Having thus described our invention, what we claim as new, and desire tosecure by Letters Patent is:
 1. A user context classifier for a customerself service system that performs resource search and selection, saidsystem including a context attribute database comprising types of usercontexts and one or more context attributes associated with each usercontext for processing by said system, and context attribute functiondatabase comprising functions for computing values for each contextattribute, said classifier comprising a mechanism for receiving a userquery and a context vector comprising data associating an interactionstate with said user and, processing said query and context vectoragainst data included in said context attribute database and contextattribute function database for predicting a particular user context,wherein said classifier populates said user context vector with contextparameters specifying a user interaction state for use in a subsequentresource search.
 2. The user context classifier for a customer selfservice system as claimed in claim 1, wherein said processing mechanismincludes mechanism for applying said functions to context for specifyingsaid user interaction state, said mechanism further annotating thecontext vector with a set of context parameters for use in subsequentprocessing.
 3. The user context classifier for a customer self servicesystem as claimed in claim 1, wherein said processing mechanismimplements an inductive learning algorithm for predicting said usercontexts.
 4. The user context classifier for a customer self servicesystem as claimed in claim 1, further including mechanism for updatingthe attribute value functions database with more enhanced functions. 5.The user context classifier for a customer self service system asclaimed in claim 1, wherein said system further includes a userinteraction database comprising data relating to past user queriesentered into the system and associated user contexts for particularusers, said mechanism for updating the attribute value functionsdatabase comprising mechanism for analyzing historical user interactiondata from the user interaction database and learning how contextattribute values map to context attribute functions, wherein said datafrom the user records database serves as a training set for continuousimprovement of said functions in said attribute function database. 6.The user context classifier for a customer self service system asclaimed in claim 5, wherein said user interaction data includes datarelating to previous system interactions, said data including uservalidated contexts that were applicable during said prior systeminteractions, and the users responses relating to those interactions. 7.The user context classifier for a customer self service system asclaimed in claim 6, wherein said previous system interaction datafurther includes prior transactions of a current user and priortransactions of other similar users, wherein common behaviors andacceptance criteria are determined for said updating said functions. 8.The user context classifier for a customer self service system asclaimed in claim 7, wherein similar users comprise those users withshared organization, community or environmental characteristics.
 9. Theuser context classifier for a customer self service system as claimed inclaim 5, wherein said updating mechanism provides additions andmodifications to a set of context attribute functions resulting inincreasing ability to predict derived contexts as functions of the rawcontexts.
 10. A method for classifying user contexts for a customer selfservice system that performs resource search and selection, said methodcomprising the steps of: a) receiving a user query and a context vectorcomprising data associating an interaction state with said user; b)processing said query and context vector against data included in acontext attribute database comprising types of user contexts and one ormore context attributes associated with each user context for processingby said system; and c) processing said query and context vector againstdata included in a context attribute function database comprisingfunctions for computing values for each context attribute, wherein saidprocessing steps b) and c) results in predicting a particular usercontext and populating said user context vector with context parametersspecifying a user interaction state for use in a subsequent resourcesearch.
 11. The method as claimed in claim 10, wherein said processingstep c) further includes the step of applying said functions to contextfor specifying said user interaction state, said populating stepincluding annotating the context vector with a set of context parametersfor use in subsequent processing.
 12. The method as claimed in claim 10,wherein said processing step c) further includes the step ofimplementing an inductive learning algorithm for predicting said usercontexts.
 13. The method as claimed in claim 10, further including thestep of updating the attribute value functions database with moreenhanced functions.
 14. The method as claimed in claim 13, wherein saidupdating step includes the steps of: analyzing historical userinteraction data from a user interaction database comprising datarelating to past user queries entered into the system and associateduser contexts for particular users; and, mapping context attributevalues to context attribute functions, said data from said user recordsdatabase serving as a training set for continuous improvement of saidfunctions in said attribute function database.
 15. The method as claimedin claim 14, wherein said user interaction data further includes datarelating to previous system interactions, said data including uservalidated contexts that were applicable during said prior systeminteractions, and the users responses relating to those interactions.16. The method as claimed in claim 15, wherein said previous systeminteractions includes prior transactions of a current user and priortransactions of other similar users, said functions updating stepincluding the step of determining common behaviors and acceptancecriteria from said previous system interactions.
 17. The method asclaimed in claim 16, wherein said similar users comprise those userswith shared organization, community or environmental characteristics.18. The method as claimed in claim 16, wherein said updating stepincludes the steps of providing additions and modifications to a set ofcontext attribute functions resulting in increasing ability to predictderived contexts as functions of raw contexts.
 19. A program storagedevice readable by machine, tangibly embodying a program of instructionsexecutable by the machine to perform method steps for classifying usercontexts for a customer self service system that performs resourcesearch and selection, said method comprising the steps of: a) receivinga user query and a context vector comprising data associating aninteraction state with said user; b) processing said query and contextvector against data included in a context attribute database comprisingtypes of user contexts and one or more context attributes associatedwith each user context for processing by said system; and c) processingsaid query and context vector against data included in a contextattribute function database comprising functions for computing valuesfor each context attribute, wherein said processing steps b) and c)results in predicting a particular user context and populating said usercontext vector with context parameters specifying a user interactionstate for use in a subsequent resource search.
 20. The program storagedevice readable by machine as claimed in claim 19, wherein saidprocessing step c) further includes the step of applying said functionsto context for specifying said user interaction state, said populatingstep including annotating the context vector with a set of contextparameters for use in subsequent processing.
 21. The program storagedevice readable by machine as claimed in claim 19, wherein saidprocessing step c) further includes the step of implementing aninductive learning algorithm for predicting said user contexts.
 22. Theprogram storage device readable by machine as claimed in claim 19,further including the step of updating the attribute value functionsdatabase with more enhanced functions.
 23. The program storage devicereadable by machine as claimed in claim 22, wherein said updating stepincludes the steps of: analyzing historical user interaction data from auser interaction database comprising data relating to past user queriesentered into the system and associated user contexts for particularusers; and, mapping context attribute values to context attributefunctions, said data from said user records database serving as atraining set for continuous improvement of said functions in saidattribute function database.
 24. The program storage device readable bymachine as claimed in claim 23, wherein said user interaction datafurther includes data relating to previous system interactions, saiddata including user validated contexts that were applicable during saidprior system interactions, and the users responses relating to thoseinteractions.